*Result*: Analysis of inspection allocation strategies for genetic manufacturing systems with a generalised nonlinear program.
*Further Information*
*Deoxyribonucleic acid (DNA) fabrication through de novo gene synthesis has been pivotal in the development of new vaccines, the creation of functionalised biomaterials, and the increased understanding of the function of cells. Although gene synthesis has advanced significantly over the past ten years, several limiting factors have slowed the rate at which these technologies have been transferred from research laboratories into full-scale industrial production. With a genetic manufacturing system (GMS), the final product consists of a genetic construct. Of particular importance is the amount of waste and repeated work observed in the DNA fabrication process. Inspection and real-time monitoring strategies are possible, but it is unclear if these techniques are cost-efficient and value-added for the successful creation of custom genetic constructs. The purpose of this paper is to study the potential costs and benefits of various inspection strategies with both type I and type II errors for a GMS utilising de novo gene synthesis. A mathematical formulation is proposed to address the problem as a multi-stage inspection allocation problem. The resulting nonlinear binary model determines the preferred inspection strategies to minimise cost or time. The results also provide useful guidance for both academic and industrial labs with GMS. [ABSTRACT FROM AUTHOR]
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